/TGRS_MLUDA-2024

code for 《Mind the Gap: Mutil-Level Unsupervised Domain Adaptation for Cross-scene Hyperspectral Image Classification》

Primary LanguagePythonGNU General Public License v3.0GPL-3.0

Mind the Gap😮: Mutil-Level Unsupervised Domain Adaptation for Cross-scene Hyperspectral Image Classification, TGRS, 2024

Mingshuo Cai,Bobo Xi, Jiaojiao Li,Shou Feng, Yunsong Li, Zan Li, and Jocelyn Chanussot.

Code for the paper: Mind the Gap: Mutil-Level Unsupervised Domain Adaptation for Cross-scene Hyperspectral Image Classification.🤩

Houston

Fig. 1. The flowchart of the MLUDA, illustrating the domain adaptation strategies at the image-, feature-, and logic-level.

Result in 3 datasets

Houston

Houtson 18

Pavia

Pavia City

SH2HZ

Hangzhou

Project Page

Now you can find more information in our page MLUDA | Project page (cfcys.github.io)!🥳

References

If you find this code helpful😊, please kindly cite:

M. Cai et al., "Mind the Gap: Multi-Level Unsupervised Domain Adaptation for Cross-scene Hyperspectral Image Classification," in IEEE Transactions on Geoscience and Remote Sensing, doi: 10.1109/TGRS.2024.3407952. keywords: {Feature extraction;Image color analysis;Convolutional neural networks;Training;Task analysis;Visualization;Hyperspectral imaging;Cross-scene;domain adaptation;guided filter;cross attention;supervised contrastive learning},

or you can give me a little⭐!

Citation Details

BibTeX entry:

@ARTICLE{10543066,
  author={Cai, Mingshuo and Xi, Bobo and Li, Jiaojiao and Feng, Shou and Li, Yunsong and Li, Zan and Chanussot, Jocelyn},
  journal={IEEE Transactions on Geoscience and Remote Sensing}, 
  title={Mind the Gap: Multi-Level Unsupervised Domain Adaptation for Cross-scene Hyperspectral Image Classification}, 
  year={2024},
  volume={},
  number={},
  pages={1-1},
  keywords={Feature extraction;Image color analysis;Convolutional neural networks;Training;Task analysis;Visualization;Hyperspectral imaging;Cross-scene;domain adaptation;guided filter;cross attention;supervised contrastive learning},
  doi={10.1109/TGRS.2024.3407952}}

Licensing

Copyright (C) 2024 Mingshuo Cai

This program is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, version 3 of the License.

This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.

You should have received a copy of the GNU General Public License along with this program.